Smart Road Condition Monitoring and Optimal Routing System Using Yolo V11
Year: 2025
Type: article
Abstract: —This project tackles the urgent problem of potholes on roads through the creation of areal-time pothole detection and map-ping system. Making use of the YOLO V11 deep learning algorithm, our system analyzes video feeds to detect potholes on the road surface accurately and efficiently. This allows for real-time alerts to drivers, enabling them to respond quickly and evade accidents. In addition, the system produces a dynamic map of identified potholes, constantly refreshed with new information. This map not only gives a visual display of road condition but also feeds into an optimal routing module. The routing system takes advantage of this real-time information to recommend safer and more efficient routes, leading drivers away from roads with high densities of potholes.Aimed for flexibility and integration into diverse vehicle platforms, the system maximizes real-time performance for efficient operation in dynamic driving conditions. Future work will target increased detection accuracy under varied conditions to further optimize the reliability and efficiency of the system. This project is a major breakthrough in road safety technology, providing an end-to-end solution for pothole detection and avoidance.
Author: Mekha Jose, Abhishek R Paleri, Athul Mohan, Avin joshy, Ali Jasim
Institution: Amal Jyothi College of Engineering
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6911940520
FWCI:
Cites:
Cited by:
Related to: